User Behavior Profile

ABSTRACT

A method, system and computer-usable medium are disclosed for generating a cyber behavior profile comprising monitoring user interactions between a user and an information handling system; converting the user interactions into electronic information representing the user interactions, the electronic information representing the user interactions comprising multi-layered electronic information, each layer of the multi-layered electronic information corresponding to a respective layer of user interaction; and generating a unique multi-dimensional cyber behavior profile based upon the multi-layered electronic information representing the user interactions.

BACKGROUND OF THE INVENTION Field of the Invention

The present invention relates in general to the field of computers andsimilar technologies, and in particular to software utilized in thisfield. Still more particularly, it relates to a method, system andcomputer-usable medium for implementing a user behavior profile.

Description of the Related Art

Users interact with physical, system, data, content and servicesresources of all kinds, as well as each other, on a daily basis. Each ofthese interactions, whether accidental or intended, could pose somedegree of security risk to the owner of such resources depending on thebehavior of the user. In particular, the actions of a trusted user maybecome malicious as a result of being subverted, compromised orradicalized due to any number of internal or external factors orstressors. For example, financial pressure, political idealism,irrational thoughts, or other influences may adversely affect a user'sintent and/or behavior. Furthermore, such an insider threat may beintimately familiar with how systems operate, how they are protected,and how weaknesses can be exploited.

Both physical and cyber security efforts have traditionally beenoriented towards preventing or circumventing external threats. Physicalsecurity approaches have typically focused on monitoring and restrictingaccess to tangible resources. Likewise, cyber security approaches haveincluded network access controls, intrusion detection and preventionsystems, machine learning, big data analysis, software patch management,and secured routers. Yet little progress has been made in addressing theroot cause of security breaches, primarily because the threat landscapeis constantly shifting faster than current thinking, which always seemsto be one step behind technological change.

In particular, current data loss prevention (DLP) approaches primarilyfocus on enforcing policies for compliance, privacy, and the protectionof intellectual property (IP). Such approaches typically cover data atrest, in motion, and in use, across multiple channels including email,endpoints, networks, mobile devices, and cloud environments. However,the efficacy of such policies typically relies on enforcement of astatic set of rules governing what a user can and cannot do with certaindata. Various approaches for attempting to detect insider threats arealso known. For example, one approach to detecting such threats includesperforming user profiling operations to infer the intent of useractions. Another approach is to perform behavioral analysis operationswhen users are interacting with a system.

Nonetheless, many organizations first turn to technology to addressinsider threats, which include malicious cyber behavior by individualswho have legitimate rights to access and modify an organization'sresources, such as systems, data stores, services and facilities. Whilethe number of malicious users may be small (e.g., less than 0.1% of allusers in an organization), they may wreak serious financial and othertypes of damage. Accordingly, some organizations have implementedvarious machine learning approaches to identify anomalous or malicioususer behavior.

However, human behavior is often unpredictable and valid machinelearning training data may be difficult to obtain. Furthermore,identifying an impersonator that appears legitimate can proveproblematic, especially if their observed interactions with resourcesare limited. Likewise, it is often difficult to detect a trusted insiderbehaving in ways that appear normal but conceal nefarious motives. Humancomputers users are subject to the normality of life to include,vacations, job detail changes, interpersonal relationship stress andother daily occurrences making traditional behavioral baseline analysisdifficult without accounting for intermittent pattern features.Moreover, organizations typically have limited technical resources todevote to an insider threat program and are constrained in the types ofdata they can proactively collect and analyze.

SUMMARY OF THE INVENTION

A method, system and computer-usable medium are disclosed for generatinga cyber behavior profile comprising monitoring user interactions betweena user and an information handling system; converting the userinteractions into electronic information representing the userinteractions, the electronic information representing the userinteractions comprising multi-layered electronic information, each layerof the multi-layered electronic information corresponding to arespective layer of user interaction; and generating a uniquemulti-dimensional cyber behavior profile based upon the multi-layeredelectronic information representing the user interactions.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention may be better understood, and its numerousobjects, features and advantages made apparent to those skilled in theart by referencing the accompanying drawings. The use of the samereference number throughout the several figures designates a like orsimilar element.

FIG. 1 depicts an exemplary client computer in which the presentinvention may be implemented;

FIG. 2 is a simplified block diagram of electronically-observable userbehavior elements and their interrelationship;

FIG. 3 is a simplified block diagram of a user behavior monitoringsystem implemented to identify acceptable, anomalous, and malicious userbehavior;

FIG. 4 is a simplified block diagram of a user behavior profileimplemented as a blockchain;

FIG. 5 is a simplified block diagram of a user behavior block in ablockchain;

FIG. 6 is a simplified block diagram of a transportable user behaviorprofile;

FIGS. 7a and 7b are a generalized flowchart of the performance of userbehavior profile origination operations; and

FIGS. 8a and 8b are a generalized flowchart of the performance of userbehavior monitoring operations to detect acceptable, anomalous, andmalicious cyber behavior.

DETAILED DESCRIPTION

A method, system and computer-usable medium are disclosed for detectingacceptable, anomalous, and malicious user behavior. For purposes of thisdisclosure, an information handling system may include anyinstrumentality or aggregate of instrumentalities operable to compute,classify, process, transmit, receive, retrieve, originate, switch,store, display, manifest, detect, record, reproduce, handle, or utilizeany form of information, intelligence, or data for business, scientific,control, or other purposes. For example, an information handling systemmay be a personal computer, a mobile device such as a tablet orsmartphone, a connected “smart device,” a network appliance, a networkstorage device, or any other suitable device and may vary in size,shape, performance, functionality, and price. The information handlingsystem may include random access memory (RAM), one or more processingresources such as a central processing unit (CPU) or hardware orsoftware control logic, ROM, and/or other types of nonvolatile memory.Additional components of the information handling system may include oneor more storage systems, one or more network ports for communicatingexternally, as well as various input and output (I/O) devices, such as akeyboard, a mouse, and a graphics display.

FIG. 1 is a generalized illustration of an information handling system100 that can be used to implement the system and method of the presentinvention. The information handling system 100 includes a processor(e.g., central processor unit or “CPU”) 102, input/output (I/O) devices104, such as a display, a keyboard, a mouse, and associated controllers,a storage system 106, and various other subsystems 108. In variousembodiments, the information handling system 100 also includes networkport 110 operable to connect to a network 140, which is likewiseaccessible by a service provider server 142. The information handlingsystem 100 likewise includes system memory 112, which is interconnectedto the foregoing via one or more buses 114. System memory 112 furtherincludes operating system (OS) 116 and in various embodiments may alsoinclude a user behavior monitoring system 118. In one embodiment, theinformation handling system 100 is able to download the user behaviormonitoring system 118 from the service provider server 142. In anotherembodiment, the user behavior monitoring system 118 is provided as aservice from the service provider server 142.

In various embodiments, the user behavior monitoring system 118 performsa detection operation to determine whether a particular behaviorassociated with a given user is acceptable, unacceptable, anomalous, ormalicious. In certain embodiments, a behavior may include variousprocesses performed at the behest of a user, such as a physical or cyberbehavior, described in greater detail herein. In various embodiments,the detection operation is performed to attribute such processes to theuser associated with the acceptable, unacceptable, anomalous, ormalicious behavior. In certain embodiments, the detection operationimproves processor efficiency, and thus the efficiency of theinformation handling system 100, by automatically identifyingacceptable, unacceptable, anomalous, or malicious behavior.

As will be appreciated, once the information handling system 100 isconfigured to perform the acceptable, unacceptable, anomalous, ormalicious behavior detection operation, the information handling system100 becomes a specialized computing device specifically configured toperform the acceptable, anomalous, or malicious behavior detectionoperation (i.e., a specialized user-centric information handling system)and is not a general purpose computing device. Moreover, theimplementation of the user behavior detection monitoring system 118 onthe information handling system 100 improves the functionality of theinformation handling system 100 and provides a useful and concreteresult of automatically detecting acceptable, anomalous, and maliciousbehavior associated with a user.

FIG. 2 is a simplified block diagram of electronically-observable userbehavior elements implemented in accordance with an embodiment of theinvention and their interrelationship. As used herein,electronically-observable user behavior broadly refers to any behaviorexhibited or enacted by a user that can be electronically observed. Invarious embodiments, user behavior may include a user's physicalbehavior, cyber behavior, or a combination thereof. As likewise usedherein, physical behavior broadly refers to any user behavior occurringwithin a physical realm, such as speaking, gesturing, facial patterns orexpressions, walking, and so forth. More particularly, physical behaviormay include any activity enacted by a user that can be objectivelyobserved, or indirectly inferred, within a physical realm.

A physical behavior element, as likewise used herein, broadly refers toa user's behavior in the performance of a particular action within aphysical realm. As an example, a user, such as user ‘A’ 202 or ‘B’ 262,may attempt to use an electronic access card to enter a securedbuilding. In this example, the use of the access card to enter thebuilding is the action and the reading of the access card makes theuser's physical behavior electronically-observable. As another example,user ‘A’ 202 may physically deliver a document to user ‘B’ 262, which iscaptured by a video surveillance system. In this example, the physicaldelivery of the document to the other user ‘B’ 262 is the action and thevideo record of the delivery makes the user's physical behaviorelectronically-observable.

Cyber behavior, as used herein, broadly refers to any user behavioroccurring within cyberspace. More particularly, cyber behavior mayinclude physical, social, or mental activities enacted by a user thatcan be objectively observed, directly or indirectly, or indirectlyinferred, within cyberspace. As likewise used herein, cyberspace broadlyrefers to a network environment, such as an internal 244 or external 246network, capable of supporting communication of information between twoor more entities. In various embodiments, the entity may be a user, suchas user ‘A’ 202 or ‘B’ 262, a user device 230, or various resources 250.In certain embodiments, the entities may include various user devices230 or resources 250 operating at the behest of a user, such as user ‘A’202 or ‘B’ 262. In various embodiments, the communication between theentities may include audio, image, video, text, or binary data.

In various embodiments, the communication of the information may takeplace in real-time or near-real-time. As an example, a cellular phoneconversation may be used to communicate information in real-time, whilean instant message (IM) exchange may be used to communicate informationin near-real-time. In certain embodiments, the communication of theinformation may take place asynchronously. For example, an email messagemay be stored on a user device 230 when it is offline. In this example,the information may be communicated to its intended recipient once theuser device 230 gains access to an internal 244 or external 246 network.

A cyber behavior element, as likewise used herein, broadly refers to auser's behavior during the performance of a particular action withincyberspace. As an example, user ‘A’ 202 may use a user device 230 tobrowse a particular web page on a news site on the Internet. In thisexample, the individual actions performed by user ‘A’ 202 to access theweb page constitute a cyber behavior element. As another example, user‘A’ 202 may use a user device 230 to download a data file from aparticular system 254. In this example, the individual actions performedby user ‘A’ 202 to download the data file, including the use of one ormore user authentication factors 204 for user authentication, constitutea cyber behavior element. In these examples, the actions are enactedwithin cyberspace, which makes them electronically-observable.

In various embodiments, a physical or cyber behavior element may includeone or more user behavior activities. In various embodiments, a userbehavior activity may be enriched by context about the object upon whichthe activity is acted. A physical or cyber behavior activity, as usedherein, broadly refers to one or more discrete actions performed by auser, such as user ‘A’ 202 or ‘B’ 262, to enact a corresponding physicalor cyber behavior element. In various embodiments, such physical orcyber behavior activities may include the use of user authenticationfactors 204, user behavior factors 212, or a combination thereof, in theenactment of a user's physical or cyber behavior. In certainembodiments, the user authentication factors 204 are used inauthentication approaches familiar to skilled practitioners of the artto authenticate a user, such as user ‘A’ 202 or ‘B’ 262. In variousembodiments, the user authentication factors 204 may include biometrics206 (e.g., a finger print, a retinal scan, etc.), security tokens 208(e.g., a dongle containing cryptographic keys), or a useridentifier/password (ID/PW) 210.

In certain embodiments, the user behavior factors 212 may include theuser's role 214 (e.g., title, position, role, etc.), the user's accessrights 216, the user's interactions 218, and the date/time/frequency 220of those interactions 218. In certain embodiments, thedate/time/frequency 220 user behavior factor 212 may be implemented asontological or societal time, or a combination thereon. As used herein,ontological time broadly refers to how one instant in time relates toanother in a chronological sense. As an example, a first user behaviorenacted at 12:00 noon on May 17, 2017 has occurred prior to a seconduser behavior enacted at 6:39 PM on May 18, 2018. Skilled practitionersof the art will recognize one value of ontological time is to determinethe order in which various user behaviors have been enacted.

As likewise used herein, societal time broadly refers to the correlationof certain user behavior elements, user behavior activities, useridentification factors 226, or user behavior factors 212 to one or moreinstants in time. As an example, user ‘A’ 202 may access a system 254 todownload a customer list at 3:47 PM on Nov. 3, 2017. Analysis of theiruser behavior profile indicates that it is not unusual for user ‘A’ 202to download the customer list on a weekly basis. However, examination oftheir user behavior profile also indicates that user ‘A’ 202 forwardedthe downloaded customer list in an email to user ‘B’ 262 at 3:49 PM thatsame day. Furthermore, there is no record in their user behavior profilethat user ‘A’ 202 has ever communicated with user ‘B’ 262 in the past.Moreover, it may be determined, as described in greater detail herein,that user ‘B’ 262 may be employed by a competitor. Accordingly, thecorrelation of user ‘A’ 202 downloading the customer list at one pointin time, and then forwarding the customer list to user ‘B’ 262 at asecond point in time shortly thereafter, is an example of societal time.

In a variation of the prior example, user ‘A’ 202 may download thecustomer list at 3:47 PM on Nov. 3, 2017. However, instead ofimmediately forwarding the customer list to user ‘B’ 262, user ‘A’ 202leaves for a two week vacation. Upon their return, they forward thepreviously-downloaded customer list to user ‘B’ 262 at 9:14 AM on Nov.20, 2017. From an ontological time perspective, user ‘A’ 202 it has beentwo weeks since they accessed a system 254 to download the customerlist. However, from a societal time perspective, they have stillforwarded the customer list to user ‘B’ 262, despite two weeks havingelapsed since the customer list was originally downloaded.

Accordingly, the correlation of user ‘A’ 202 downloading the customerlist at one point in time, and then forwarding the customer list to user‘B’ 262 at a much later point in time, is another example of societaltime. More particularly, it may be inferred that the intent of user ‘A’202 did not changed during the two weeks they were on vacation.Furthermore, user ‘A’ 202 may have attempted to mask an intendedmalicious act by letting some period of time elapse between the timethey originally downloaded the customer list and when they eventuallyforwarded it to user ‘B’ 262. From the foregoing, those of skill in theart will recognize that the use of societal time may be advantageous indetermining whether a particular user behavior is acceptable, anomalousor malicious.

In various embodiments, the user behavior factors 212 may likewiseinclude the user's location 222 when the interactions 218 are enacted,and user gestures 224 used to enact the interactions 218. In certainembodiments, the user gestures 224 may include key strokes on a keypad,a cursor movement, a mouse movement or click, a finger swipe, tap, orother hand gesture, an eye movement, or some combination thereof. Invarious embodiments, the user gestures 224 may likewise include thecadence of the user's keystrokes, the motion, force and duration of ahand or finger gesture, the rapidity and direction of various eyemovements, or some combination thereof. In one embodiment, the usergestures 224 may include various audio or verbal commands performed bythe user.

In various embodiments, the user behavior factors 212 may includeadditional context associated with the captured behavior of the user.For example, the additional context might indicate the user was onvacation, the user is in a new job role, the user is being terminated in30 days, and so forth. Additionally, the additional context could bemore complex to include changes in user communication relationships orsemantics of created content and communications. In certain embodiments,the additional context might include tags to verbosely contextualize asmaller design element. In certain embodiments, the tags may begenerated from meta analytic sources. In certain embodiments, theadditional context may be tagged post-event and then associated withvarious user behavior factors. In certain embodiments, the associationof the additional context may be accomplished via a blockchain blockwithin a user behavior profile blockchain, described in greater detailherein, implemented with appropriate time stamping to allow forversioning over time.

In certain embodiments, the user interactions 218 may includeuser/device 228, user/network 242, user/resource 248, user/user 260interactions, or some combination thereof. In various embodiments, theuser/device 228 interactions include an interaction between a user, suchas user ‘A’ 202 or ‘B’ 262 and a user device 230. As used herein, a userdevice 230 refers to an information processing system such as a personalcomputer, a laptop computer, a tablet computer, a personal digitalassistant (PDA), a smart phone, a mobile telephone, or other device thatis capable of processing and communicating data. In certain embodiments,the user device 230 is used to communicate data through the use of aninternal network 244, an external network 246, or a combination thereof.

In various embodiments, the cyber behavior element may be based upon amachine readable representation of some, or all of, one or more useridentification factors 226. In various embodiments, the useridentification factors 226 may include biometric information,personality type information, technical skill level, financialinformation location information, peer information, social networkinformation, or a combination thereof. Examples of personality typeinformation include various descriptor information commonly associatedwith Jungian, Meyers-Briggs Type Indicator (MBTI), NEO PersonalityInventory (NEO PI-I), five factor model (FFM), and other knownapproaches to describing personality types.

The user identification factors 226 may likewise include travel-relatedinformation, expense account information, paid time off (PTO)information, data analysis information, personally sensitive information(PSI), personally identifiable information (PII), or a combinationthereof. Likewise, the user identification factors 226 may includeinsider information, configuration information, third party information,or a combination thereof. Skilled practitioners of the art willrecognize that many such embodiments are possible. Accordingly, theforegoing is not intended to limit the spirit, scope or intent of theinvention.

In certain embodiments, the user device 230 is configured to receivelocation data 236, which is used as a data source for determining theuser's location 222. In one embodiment, the location data 236 mayinclude Geographical Positioning System (GPS) data provided by a GPSsatellite 238. In another embodiment the location data 236 may includelocation data 236 provided by a wireless network, such as from acellular network tower 240. In yet another embodiment (not shown), thelocation data 236 may include various Internet Protocol (IP) addressinformation assigned to the user device 230. In yet still anotherembodiment (also not shown), the location data 236 may includerecognizable structures or physical addresses within a digital image orvideo recording.

In various embodiments, the user devices 230 may also include an inputdevice (not shown), such as a keypad, magnetic card reader, tokeninterface, biometric sensor, digital camera, video surveillance camera,and so forth. In these embodiments, such user devices 230 may bedirectly, or indirectly, connected to a particular facility 252 orsystem 254. As an example, the user device 230 may be directly connectedto an ingress/egress system, such as an electronic lock on a door or anaccess gate of a parking garage. As another example, the user device 230may be indirectly connected to a physical security mechanism through adedicated security network.

In certain embodiments, the user/device 228 interaction may includeinteraction with a user device 230 that is not connected to a network atthe time the interaction occurs. As an example, user ‘A’ 202 or ‘B’ 262may interact with a user device 230 that is offline, using applications232, accessing data 234, or a combination thereof, it contains. Thoseuser/device 228 interactions, or their result, may be stored on the userdevice 230 and then be accessed or retrieved at a later time once theuser device 230 establishes a connection to the internal 244 or external246 networks.

In various embodiments, the user/network 242 interactions may includeinteractions with an internal 244 network, an external 246 network, orsome combination thereof. In these embodiments, the internal 244 and theexternal 246 networks may include a public network, such as theInternet, a physical private network, a virtual private network (VPN),The Onion Router (TOR) network (used for enabling anonymouscommunication), or any combination thereof. In certain embodiments, theinternal 244 and external 246 networks may likewise include a wirelessnetwork, including a personal area network (PAN), based on technologiessuch as Bluetooth. In various embodiments, the wireless network mayinclude a wireless local area network (WLAN), based on variations of theIEEE 802.11 specification, commonly referred to as WiFi. In certainembodiments, the wireless network may include a wireless wide areanetwork (WWAN) based on an industry standard including various 3G, 4Gand 5G technologies.

In certain embodiments the user/resource 248 interactions may includeinteractions with various resources 250. In certain embodiments, theresources 250 may include various facilities 252 and systems 254, eitherof which may be physical or virtual, as well as data stores 256 andservices 258. In various embodiments, the user/user 260 interactions mayinclude interactions between two or more users, such as user ‘A’ 202 and‘B’ 262. In these embodiments, the user/user interactions 260 may bephysical, such as a face-to-face meeting, via a user/device 228interaction, a user/network 242 interaction, a user/resource 248interaction, or some combination thereof.

In one embodiment, the user/user 260 interaction may include aface-to-face verbal exchange between two users. In another embodiment,the user/user 260 interaction may include a written exchange, such astext written on a sheet of paper, between two users. In yet anotherembodiment, the user/user 260 interaction may include a face-to-faceexchange of gestures, such as a sign language exchange, between twousers. Those of skill in the art will recognize that many such examplesof user/device 228, user/network 242, user/resource 248, and user/user260 interactions are possible. Accordingly, the foregoing is notintended to limit the spirit, scope or intent of the invention.

In certain embodiments, the user authentication factors 204 are used incombination to perform multi-factor authentication of a user, such asuser ‘A’ 202 or ‘B’ 262. As used herein, multi-factor authenticationbroadly refers to approaches requiring two or more authenticationfactors. In general, multi-factor authentication includes three classesof user authentication factors 204. The first is something the userknows, such as a user ID/PW 210. The second is something the userpossesses, such as a security token 208. The third is something that isinherent to the user, such as a biometric 206.

In various embodiments, multi-factor authentication is extended toinclude a fourth class of factors, which includes one or more userbehavior factors 212, one or more user identification factors 226, or acombination thereof. In these embodiments, the fourth class of factorsincludes user behavior elements the user has done, is currently doing,or is expected to do in the future. In certain embodiments, multi-factorauthentication is performed on recurring basis. In one embodiment, themulti-factor authentication is performed at certain time intervalsduring the enactment of a particular user behavior. In anotherembodiment, the time interval is uniform. In yet another embodiment, thetime interval may vary or be random. In yet still another embodiment,the multi-factor authentication is performed according to the enactmentof a particular user behavior, such as accessing a different resource250.

In various embodiments, certain combinations of the enhancedmulti-factor authentication described herein are used according to theenactment of a particular user behavior. From the foregoing, those ofskill in the art will recognize that the addition of such a fourth classof factors not only strengthens current multi-factor authenticationapproaches, but further, allows the factors to be more uniquelyassociated with a given user. Skilled practitioners of the art willlikewise realize that many such embodiments are possible. Accordingly,the foregoing is not intended to limit the spirit, scope or intent ofthe invention.

FIG. 3 is a simplified block diagram of a user behavior monitoringsystem implemented in accordance with an embodiment of the invention todetect acceptable, anomalous, and malicious user behavior. In variousembodiments, user behavior profiles ‘1’ 372 through ‘n’ 374 arerespectively generated, as described in greater detail herein, for users‘1’ 302 through ‘n’ 304. As used herein, a user behavior profile (alsoreferred to as a cyber behavior profile) broadly refers to a collectionof various enactments of user behavior associated with a particularuser, such as users ‘1’ 302 through ‘n’ 304.

In certain embodiments, as described in greater detail herein,individual enactments of user behavior may be represented as one or moreuser behavior elements, which in turn may be associated with acorresponding user behavior profile. In certain embodiments, as likewisedescribed in greater detail herein, individual behavior elements mayinclude one or more user behavior activities, which in turn may refer toone or more activities performed by a user. Such activities may includethe use of one or more user authentication, identification or behaviorfactors, likewise described in greater detail herein.

In certain embodiments, a user behavior profile may be implemented as amulti-faceted user behavior profile, where each facet corresponds to aparticular user authentication, identification or behavior factor. As anexample, one facet of a multi-faceted user behavior profile maycorrespond to the use of a particular biometric authentication factor,while another facet may correspond to a user's access rights to acertain system. In certain embodiments, a multi-faceted user behaviorprofile may be further implemented as a multi-dimensional user behaviorprofile, where each user authentication, identification or behaviorfactor associated with a facet may have a corresponding degree ofdimensional detail.

As an example, a biometric authentication factor associated with aretinal scan may simply have the dimension of “match” or “not match,”which provides a low degree of dimensional detail. Conversely, itsassociated dimension information may include actual retinal patterncorrelation scores, which provides a higher degree of dimensionaldetail. As yet another example, a user behavior factor associated with auser gesture, such as keyboard cadence, may simply indicate whether theuser's keyboard usage is within an acceptable range of rhythm and speedmetrics, which provides a low degree of dimensional detail. In contrast,its associated dimensional information may include key loggerinformation related to which keys were struck, in which order, at whichpoint in time, which provides a higher degree of dimensional detail.

As yet another example, a user behavior factor associated withdate/time/frequency, such as when a particular file is accessed, maysimply indicate which date the file was accessed, but not the exact timeor how often. Alternatively, its associated dimensional information mayinclude exact times the file was accessed, which by extension mayindicated how frequent or infrequently the file was accessed during aparticular temporal interval. In this example, the lack of the exacttime or how often the file was accessed provides a low degree ofdimensional detail. Conversely, its provision provides a high degree ofdimensional detail, which may prove advantageous when assessing riskassociated with the user accessing the file.

In certain embodiments, a user behavior profile may be implemented as amulti-layered user behavior profile, where each layer corresponds to acertain level of detail corresponding to a particular userauthentication, identification or behavior factor. In certainembodiments, the certain level of detail corresponds to a certain levelof temporal detail corresponding to a particular user authentication,identification or behavior factor. As an example, one temporal detaillayer of a multi-layered user behavior profile may correspond to a userbehavior factor associated with user interactions, described in greaterdetail herein, over a 30 day period. In this example, the various userinteractions enacted during the 30 day period may be abstracted tosimply represent which user/device 228, user/network 242, user/resource248, and user/user 260 interactions took place, with their correspondingfrequency. Alternatively, another temporal detail layer may provide thedate/time/frequency of each interaction, not just during the 30 dayperiod, but each 24 hour period therein. It will be appreciated thatsuch a temporal level of detail related to such interactions may provideuseful trend information, which in turn can be used advantageously whenassessing security risk.

It will be appreciated that over time, the user behavior of a particularuser, such as user ‘A’ 202, will be uniquely different and distinct fromanother user, such as user ‘B’ 262. Accordingly, user behavior profile‘1’ 372 will uniquely reflect the user behavior of user ‘1’ 302, just asuser behavior profile ‘n’ 374 will uniquely reflect the user behavior ofuser ‘n’ 310. As an example, user ‘A’ 202 may have a user role of salesadministrator. Upon arriving at their office in the morning, the userconsistently checks their email, item by item, responding to each inturn, followed by processing expense reports for field sales personnel.Then, after lunch, the user may access and review sales forecasts on aninternal system 254. Furthermore, the user may exhibit sporadic keyboardentry interspersed with extensive mouse activity, or user gestures, whenperusing the sales forecasts. Moreover, personality type informationassociated with user ‘A’ 202 may indicate the user consistently exhibitsa positive, outgoing attitude. In this example, the sequence of theactivities enacted by user ‘A’ 202 throughout the day, and theirfrequency, correspond to the date/time/frequency 220 user behaviorfactor described in the descriptive text associated with FIG. 2.Likewise, the keyboard cadence and other user gestures are examples ofgranular user behavior factors, while the personality type informationis an example of an abstract user behavior factor.

As another example, user ‘B’ 262 may have a user role of financialcontroller. Upon arriving at their office in the morning, the userusually scans their email messages, responding only to those that areurgent. Then they check the daily budget status of each department tosee whether they are conforming to their respective guidelines. Afterlunch, the user may follow up on emails that are less urgent, followedby updating the organization's financials, likewise on an internalsystem 254. Additionally, the user may exhibit deliberate keyboard entryinterspersed with iterative mouse activity, or user gestures, whenupdating financial information. Moreover, personality type informationassociated with user ‘B’ 262 may indicate they consistently exhibit areserved, introspective and contemplative attitude. As in the priorexample, the sequence of the activities enacted by user ‘B’ 262throughout the day, and their frequency, correspond to thedate/time/frequency 220 user behavior factor described in thedescriptive text associated with FIG. 2. Likewise, as before, thekeyboard cadence and other user gestures are examples of granular userbehavior factors, while the personality type information is an exampleof an abstract user behavior factor.

It will likewise be appreciated that the user behavior of a particularuser may evolve over time. As an example, certain user behaviorexhibited by a user during the first month of assuming a new positionwithin an organization may be quite different than the user behaviorexhibited after being in the position for six months. To continue theexample, the user may be somewhat tentative when learning to access andinteract with unfamiliar resources 250 in the first month in theposition, but by the sixth month, such access and interaction iscommonplace and routine.

In various embodiments, a user behavior monitoring system 118 isimplemented to observe user behavior 306 at one or more points ofobservation within a cyberspace environment. In certain embodiments, thepoints of observation may occur during various user interactions, suchas user/device 228, user/network 242, user/resource 248, and user/user260 interactions described in greater detail herein. As an example, auser/user 260 interaction may include an interaction between anindividual user ‘1’ 302 through ‘n’ 304 with user ‘x’ 314. In certainembodiments, the point of observation may include cyber behavior ofvarious kinds within an internal 244 network. As an example, cyberbehavior within an internal 244 network may include a user accessing aparticular internal system 254 or data store 256. In certainembodiments, the point of observation may include cyber behavior ofvarious kinds within an external 246 network. As an example, cyberbehavior within an external 246 network may include a user's socialmedia activities or participation in certain user forums.

In various embodiments, the user behavior profile ‘1’ 372 through ‘n’374 associated with a given user, such as user ‘1’ 302 through ‘n’ 304,is used by the user behavior monitoring system 118 to compare the user'scurrent user behavior 306 to past user behavior 306. If the user'scurrent user behavior 306 matches past user behavior 306, then the userbehavior monitoring system 118 may determine that the user's userbehavior 306 is acceptable 308. If not, then the user behaviormonitoring system 118 may determine that the user's user behavior 306 isanomalous 310 or malicious 312.

However, as described in greater detail herein, a change in a particularuser's user behavior 306 over time may not be anomalous 310 or malicious312. Instead, it may be acceptable 308 behavior that simply evolves overtime as a natural result of day-to-day user/device 228, user/network242, user/resource 248, or user/user 260 interactions. In certainembodiments, the user behavior monitoring system 118 is implemented todetermine whether such changes in a user's user behavior 306 over timeare acceptable 308, anomalous 310, or malicious 312. In certainembodiments, a multi-layered user behavior profile may be implemented incombination with the user behavior monitoring system 118 to make thistemporal determination. In certain embodiments, a multi-faceted ormulti-dimensional user behavior profile may likewise be implemented incombination with a multi-layer user behavior profile and the userbehavior monitoring system 118 to make such determinations. In theseembodiments, the method by which the multi-faceted, multi-dimensional,or multi-layered user behavior profile is implemented with the userbehavior monitoring system 118 is a matter of design choice.

It will be appreciated that anomalous 310 user behavior 306 may includeinadvertent or compromised user behavior 306. For example, the user mayhave innocently miss-entered a request for data that is proprietary toan organization. As another example, the user may be attempting toaccess confidential information as a result of being compromised. As yetanother example, a user may attempt to access certain proprietary datafrom their home, over a weekend, and late at night. In this example, theuser may be working from home on a project with an impending deadline.Accordingly, the attempt to access the proprietary data is legitimate,yet still anomalous 310 as the attempt did not occur during the week,from the user's place of employment, during normal work hours. However,the user behavior 306 may manifest in context with consistent remoteaccess patterns and provide sufficient evidence to determine the natureof activity.

Likewise, the user behavior monitoring system 118 may determine that theuser's user behavior 306 to be malicious 312. As yet another example, animpostor may be attempting to pose as a legitimate user in an attempt toexploit one or more resources 250. In this example, the attempt toexploit one or more resources 250 is malicious 312 user behavior 306. Asyet still another example, a legitimate user may be attempting toincrease their level of access to one or more resources 250. In thisexample, the user's attempt to increase their level of access ismalicious 312 user behavior 306.

To further extend these examples, such resources may include variousfacilities 252, systems 254, data stores 256, or services 258. Invarious embodiments, the user behavior monitoring system 118 may beimplemented to block a user if it is determined their user behavior 306is anomalous 310 or malicious 312. In certain embodiments, the userbehavior monitoring system 118 may be implemented modify a requestsubmitted by a user if it is determined the request is anomalous 310 ormalicious 312. In various embodiments, the user behavior system 118 maybe implemented to modify an outcome. For example, the user behaviorsystem 118 may encrypt a file when a copy operation is detected.

In one embodiment, the user behavior monitoring system 118 may beimplemented as a stand-alone system. In another embodiment, the cyberbehavior monitoring system 118 may be implemented as a distributedsystem. In yet another embodiment, the cyber behavior monitoring system118 may be implemented as a virtual system, such as an instantiation ofone or more virtual machines (VMs). In yet still another embodiment, theuser behavior monitoring system 118 may be implemented as a userbehavior monitoring service 366. Skilled practitioners of the art willrecognize that many such embodiments and examples are possible.Accordingly, the foregoing is not intended to limit the spirit, scope orintent of the invention.

In various embodiments, user behavior detection operations are initiatedby first authenticating a user, such as user ‘1’ 302 through ‘n’ 304.Once authenticated, the user's respective user behavior profile isretrieved, followed by ongoing monitoring of the user's user behavioractivities. The user's user behavior activities are then processed todetermine an associated user behavior element, which in turn is comparedto the user's user behavior profile. In various embodiments, the userbehavior profile is continually amended and refined based on thecontinuous interaction with the system over time.

A determination is then made whether the user's current user behaviorelement is acceptable. If so, then the user's current user behaviorelement is marked as acceptable. It will be appreciated that in variousembodiments, otherwise acceptable behavior may be determined to beanomalous or malicious in certain situations. For example, the printingor copying of a single document may be acceptable whereas when printingor copying of a large number of documents might suggest a determinationof anomalous or malicious. Otherwise, a determination is made whetherthe user's current user behavior element is anomalous. If so, then theuser's current user behavior element is marked as anomalous, followed bythe performance of anomalous user behavior operations. In variousembodiments, the anomalous user behavior operations can include ananomalous user behavior notification operation and/or an anomalous userresponse operation. In various embodiments, the anomalous user responseoperation can include a user blocking operation where an action is takento restrict or remove user access to some or all of the user devices 230and/or resources 250 and/or a risk level adjustment operation where arisk score associated with the user is adjusted based upon the anomalousbehavior. In one embodiment, the anomalous user behavior element isstored for later review. In another embodiment, a security administrator368 is notified of the anomalous user behavior element.

However, if it was determined that the user's current user behaviorelement was not anomalous, then it is marked as malicious (orunacceptable), followed by the performance of malicious behavioroperations. In various embodiments, the malicious user behavioroperations can include a malicious user behavior notification operationand/or a malicious user behavior response operation. In variousembodiments, the malicious user response operation can include a userblocking operation where an action is taken to restrict or remove useraccess to some or all of the user devices 230 and/or resources 250and/or a risk level adjustment operation where a risk score associatedwith the user is adjusted based upon the anomalous behavior. In oneembodiment, the malicious user behavior element is stored for laterreview. In another embodiment, a security administrator 368 is notifiedof the malicious user behavior element. Thereafter, the current userbehavior element, whether marked acceptable, anomalous, or malicious, isappended, as described in greater detail herein, to the user's userbehavior profile. Once the user's user behavior activities haveconcluded, user behavior profile scoring and hashing operations,likewise described in greater detail herein, are performed torespectively generate a user behavior profile score and hash. Theresulting user behavior profile score and hash are then appended to theuser's user behavior profile. It will be appreciated that any order ofthe determination of whether a behavior element is acceptable, anomalousand malicious is contemplated.

In various embodiments, user behavior profiles are stored in arepository of user behavior profiles 370. In one embodiment, therepository of user behavior profiles 370 is implemented for use by asingle user behavior monitoring system 118. In another embodiment, therepository of user behavior profiles 370 is implemented for use by aplurality of user behavior monitoring systems 118. In yet anotherembodiment, the repository of user behavior profiles 370 is implementedfor use by a user behavior monitoring service 366. Skilled practitionersof the art will recognize that many such embodiments are possible.Accordingly, the foregoing is not intended to limit the spirit, scope orintent of the invention.

In various embodiments, a user behavior profile (e.g., user behaviorprofile 372) may identify known good behavior. In various embodiments,known good interactions between a user and an information handlingsystem may be used to generate a user behavior profile identifying knowngood behavior. In various embodiments, the known good behaviorcorresponds to acceptable behavior 308. In various embodiments,additional interactions between the user and the user device aremonitored to determine whether the additional interactions correspond tothe known good behavior. In certain embodiments, the user behaviormonitoring system 118 may perform an enforcement operation when theadditional interactions do not correspond to the known good behavior. Incertain embodiments, the enforcement operations can include anythingfrom a denial of service to logging the interactions to generating anotification to a security administrator 368 regarding the interactions.

FIG. 4 is a simplified block diagram of a user behavior profileimplemented in accordance with an embodiment of the invention as ablockchain. As used herein, a blockchain broadly refers to adecentralized, distributed data structure whose contents may bereplicated across a number of systems. These contents are stored in achain of fixed structures commonly referred to as “blocks,” such as userbehavior block ‘1’ 410, block ‘2’ 412, and so forth, through block ‘n’414. Each of these blocks contains certain information about itself,such as a unique identifier, a reference to its previous block, and ahash value generated from the data it contains. As an example, userbehavior block ‘2’ 412 would contain a reference to user behavior block‘1’ 410, yet their respective hashes values would be different as theycontain different data.

Those of skill in the art will be aware that blockchains may beimplemented in different ways and for different purposes. However, thesedifferent implementations typically have certain common characteristics.For example, in certain instantiations blockchains are generallydistributed across various systems, each of which maintains a copy ofthe blockchain. Updates to one copy of the blockchain, such as theaddition of a user behavior block ‘n’ 414, results in correspondingupdates to the other copies. Accordingly, the contents of theblockchain, including its most recent updates, are available to allparticipating users of the blockchain, who in turn use their own systemsto authenticate and verify each new block. This process ofauthentication and verification ensures that the same transaction doesnot occur more than once. Furthermore with distributed types of blockchains, the legitimacy of a given block, and its associated contents, isonly certified once a majority of participants agree to its validity.

In general, the distributed and replicated nature of a blockchain, suchas a user behavior blockchain 408, makes it difficult to modifyhistorical records without invalidating any subsequent blocks addedthereafter. As a result, the user behavior data within a given userbehavior blockchain 408 is essentially immutable and tamper-evident.However, this immutability and tamper-evidence does not necessarilyensure that the user behavior data recorded in the cyber behaviorblockchain 408 can be accepted as an incontrovertible truth. Instead, itsimply means that what was originally recorded was agreed upon by amajority of the user behavior blockchain's 408 participants.

Additionally in certain embodiments, every transaction in a blockchainis serialized (i.e., stored in a sequence). Additionally in certainembodiments, every transaction in a block chain is time-stamped, whichis useful for tracking interactions between participants and verifyingvarious information contained in, or related to, a blockchain.Furthermore, instructions can be embedded within individual blocks of ablockchain. These instructions, in the form of computer-executable code,allow transactions or other operations to be initiated if certainconditions are met.

Referring now to FIG. 4, groups of user behavior activities 402,described in greater detail herein, are combined in various embodimentsto generate one or more associated user behavior elements 404, likewisedescribed in greater detail herein. In certain embodiments, theresulting one or more user behavior elements 404 are in turn combined togenerate a user behavior block, such as user behavior block ‘n’ 414. Theresulting user behavior block is then appended to a target user behaviorblockchain, such as user behavior blockchain 408. As used herein, a userbehavior block broadly refers to a blockchain block implemented tocontain various user behavior data. As likewise used herein, userbehavior data broadly refers to any data associated with a user's userbehavior, as described in greater detail herein.

In various embodiments, a user behavior blockchain 408 is implemented tocontain one or more user behavior profiles 406, described in greaterdetail herein. In one embodiment, the user behavior blockchain 408contains a single user behavior profile 406, which in turn is associatedwith an individual user. In this embodiment, user behavior blocks ‘1’410 and ‘2’ 412 through ‘n’ 414 are associated with the individual user.In another embodiment, the user behavior blockchain 408 is implementedto include user behavior profiles 406 associated with two or more users.In this embodiment, individual user behavior blocks ‘1’ 410 and ‘2’ 412through ‘n’ 414 are respectively associated with two or more userbehavior profiles 406, which in turn are respectively associated with aparticular user. In certain embodiments, the user behavior blockchain408 is parsed to identify which of the user behavior blocks ‘1’ 410 and‘2’ 412 through ‘n’ 414 are associated with a given user behaviorprofile 406, which in turn are respectively associated with a particularuser.

In various embodiments, data associated with a given user behaviorblockchain 408 is used in the performance of user behavior monitoringoperations to detect acceptable, anomalous, and malicious behaviorenacted by a user. In certain embodiments, the performance of these userbehavior monitoring operations involve comparing a newly-generated userbehavior block, such as user behavior block ‘n’ 414 topreviously-generated user behavior blocks, such as user behavior blocks‘1’ 410 and ‘2’ 412.

In certain embodiments, if the contents of the user behavior block ‘n’414 are substantively similar to the contents of user behavior blocks‘1’ 410 and ‘2’ 412, then the behavior of the user may be judged to beacceptable. However, if the contents of the user behavior block ‘n’ 414are substantively dissimilar to the contents of user behavior blocks ‘1’410 and ‘2’ 412, then the behavior of the user may be judged to beanomalous or malicious. In these embodiments, the method by which thecontents of user behavior block ‘n’ 414 are determined to besubstantively similar, or dissimilar, to the contents of user behaviorblocks ‘1’ 410 and ‘2’ 412 is a matter of design choice.

FIG. 5 is a simplified block diagram of a user behavior block in ablockchain implemented in accordance with an embodiment of theinvention. In various embodiments, a blockchain user behavior blockchain408, as shown in FIG. 4, may contain one or more user behavior blocks502, such as user behavior block ‘1’ 410, ‘2’ 412, and so forth through‘n’ 414, likewise shown in FIG. 4. In these embodiments, each userbehavior block 502 may include either or both data and metadata, such asa block reference identifier (ID) 504, a hash value of the prior userbehavior block's header 506 information, the public key of the recipient508 of the user behavior blockchain 408 transaction, and the digitalsignature of the originator 510 of the user behavior blockchain 408transaction. The user behavior block 502 may likewise include additionaleither or both data and metadata, such as a user behavior blockchaintransaction identifier 512, a transaction payload 514, and a transactiontimestamp 516.

In certain embodiments, the transaction payload 514 may include one ormore user behavior profiles 518. In various embodiments, a user behaviorprofile 518 may include various user behavior elements 524, described ingreater detail herein, and a hash 520 value of the user behaviorelements 524. In certain embodiments, the hash 520 value is implementedto determine whether the integrity of the user behavior elements 524 hasbeen compromised. In various embodiments, the user behavior profile 518may include executable code 526. In certain embodiments, the executablecode 526 may be used by a user behavior monitoring system, described ingreater detail herein, to detect acceptable, anomalous, and maliciousbehavior being enacted by a user. In various embodiments, user behaviordata contained in one or more user behavior elements 524 is used incombination with the executable code to perform user behavior monitoringoperations, likewise described in greater detail herein.

In certain embodiments, the executable code 526 can include stateinformation such as pre-calculated information associated with one ormore user behavior elements 524. In certain embodiments, the executablecode 526 can include a model of good behavior (e.g., known goodbehavior) which is used when detecting acceptable, anomalous, andmalicious behavior being enacted by a user. In certain embodiments, themodel includes a series of rules of behaviors that might lead to adetermination regarding trustworthiness. In certain embodiments, theseries of rules can include communication related rules, data movementrelated rules and/or programming modification type rules. In certainembodiments, such a model may be implemented to enable a user behaviormonitoring system to assess the intent of a user. In certainembodiments, the executable code 526 may include instructions that maybe implemented to notify a user behavior monitoring system if certainuser behavior associated with a first user behavior block 502 isinconsistent with a second user behavior block 502.

In certain embodiments, the user behavior block 502 may also contain arisk score 522. In certain embodiments, the risk score 522 includes auser behavior score. In various embodiments, the risk score 522 may beused by a user behavior monitoring system to assess the state (e.g., therisk or trustworthiness) of a particular user while enacting a givenuser behavior. In certain embodiments, the state may also be storedwithin the user behavior block 502. In certain embodiments, the state isassessed at a specific time and has a time associated with the state. Inone embodiment, the user behavior score 522 might be associated with aparticular user behavior element, such as accessing sensitive humanresource documents. In one embodiment, the user behavior score 522 mightbe related to a user's overall user behavior. In various embodiments,the user behavior block 502 may also contain information regarding howthe user behavior score was generated such as the model that was used togenerate the user behavior score 522. Storing this information providesa historical view of how the score was generated when the score wasgenerated. This information can be useful in identifying what type ofuser behavior led to the user behavior score (e.g., what was theanomaly).

As an example, a user may have a high user behavior score 522 forgeneral cyberspace activity, but a low user behavior score 522 foraccessing an organization's financial data. To continue the example, theuser's role in the organization may be related to maintaining a physicalfacility. In that role, the user may requisition cleaning supplies andschedule other users to perform maintenance. Accordingly, attempting toaccess the organization's financial data, particularly over a weekend,would indicate anomalous, or possibly malicious, behavior. To furthercontinue the example, such an attempt may result in a low user behaviorscore 522 being assigned to that particular user behavior element. Thoseof skill in the art will recognize that many such embodiments andexamples are possible. Accordingly, the foregoing is not intended tolimit the spirit, scope or intent of the invention. In certainembodiments, the user behavior score 522 may change as a result ofinformation obtained from a third party and not just from observablebehavior. For example, in another type of score if a credit score of auser changes, or the user performs a wire transfer to a known suspiciouslocation, then the user behavior score 522 may be changed based uponthis information.

In certain embodiments, the transaction timestamp 516 may be implementedto provide temporal information to a user behavior monitoring system. Incertain embodiments, the temporal information may be implemented in amulti-layer user behavior profile, described in greater detail herein.In certain embodiments, the temporal information may be used by the userbehavior monitoring system to compare current user behavior to past userbehavior, as likewise described in greater detail herein. In certainembodiments, the results of such comparisons may indicate whether thecurrent user behavior is acceptable, anomalous or malicious.

As an example, comparison of two user behavior blocks 502, one generated90 days in the past and the other 60 days in the past, exhibitconsistent user behavior. However, comparison of a user behavior block502 generated within the last 24 hours to the two previously-generateduser behavior blocks 502 indicates inconsistent user behavior.Accordingly, the inconsistent user behavior associated with the mostrecently generated user behavior block may be anomalous or malicious.

FIG. 6 is a simplified block diagram of a transportable user behaviorprofile implemented in accordance with an embodiment of the invention.In this embodiment, a user behavior profile 406 for a user 602 may beimplemented as a user behavior blockchain 408, as shown in FIG. 4. Invarious embodiments a first copy of the user behavior profile 406,profile copy ‘1’ 604 is used by a first system, system ‘1’ 606, andadditional copies, profile copy ‘n’ 608, are used by additional systems‘n’ 608 to perform various user behavior monitoring operations. Incertain embodiments, additions to profile copy ‘1’ 604 of the userbehavior profile 408 results in the same additions to profile copies ‘n’608. As a result, systems ‘1’ 606 through ‘n’ 608 are kept in synchregarding the user's 602 user behavior. Accordingly, each system ‘1’ 604through ‘n’ 610 is apprised of any anomalous or malicious user behaviorenacted by the user 602, regardless of which system was being used whenthe anomalous or malicious behavior occurred.

FIGS. 7a and 7b are a generalized flowchart of the performance of userbehavior profile origination operations in accordance with an embodimentof the invention. In this embodiment, user behavior profile originationoperations are begun in step 702, followed by the selection of a targetuser in step 706 for user behavior profile origination. An unpopulateduser behavior profile is then generated for the selected user in step706, followed by the identification of known user behavior elementsassociated with the selected user in step 708.

A user behavior element associated with the user is then selected forvalidation in step 710, followed by the performance of user behaviorvalidation operations in step 712 to determine whether the selected userbehavior element is suspect. In various embodiments, the method by whichthe user behavior element is validated is a matter of design choice. Adetermination is then made in step 714 whether the user behavior elementis suspect. If so, then the user behavior element is appended as asuspect user behavior element to the user's user behavior profile instep 716. Otherwise, the user behavior element is appended to the user'suser behavior profile in step 718.

Thereafter, or once the suspect user behavior element is appended to theuser's user behavior profile in step 716, a determination is made instep 720 whether to select another user behavior element for validation.If so, the process is continued, proceeding with step 710. Otherwise,user behavior elements that have been appended to the user behaviorprofile are processed in step 722 to generate a user behavior hashvalue, described in greater detail herein. Then, in step 724, the userbehavior elements that have been appended to the user behavior profileare processed to generate a user behavior score, likewise described ingreater detail herein. The resulting user behavior hash value and scoreare then appended to the user behavior profile in step 726.

In turn, the user behavior profile is stored in step 728 for use in userbehavior monitoring operations. In one embodiment, the user behaviorprofile is stored in a repository of user behavior profiles. In anotherembodiment, the repository of user behavior profiles is implemented foruse by a single user behavior monitoring system. In yet anotherembodiment, the repository of user behavior profiles is implemented foruse by a plurality of user behavior monitoring systems. In variousembodiments, the user behavior profile is stored in a user behaviorblockchain, described in greater detail herein. A determination is thenmade in step 730 whether to end user behavior profile originationoperations. If not, the process is continued, proceeding with step 704.Otherwise, user behavior profile origination operations are ended instep 732.

FIG. 8 is a generalized flowchart of the performance of user behaviormonitoring operations implemented in accordance with an embodiment ofthe invention to detect acceptable, anomalous, and malicious userbehavior. In this embodiment, user behavior monitoring operations arebegun in step 802, followed by the performance of user authenticationoperations, familiar to those of skill in the art, in step 804. Then, instep 806, the user's user behavior profile is retrieved, followed by theongoing monitoring of the user's user behavior activities in step 808.The user's user behavior activities are processed in step 810 todetermine their associated user behavior element, which is then comparedto the user's user behavior profile in step 812.

A determination is then made in step 814 whether the user's current userbehavior element is acceptable. If so, then the user behavior element ismarked as acceptable in block 816. Otherwise, a determination is made instep 818 whether the user's current user behavior element is anomalous.If so, then the current user behavior element is marked as anomalous instep 820, followed by the performance of anomalous user behavioroperations in step 822. In one embodiment, the anomalous user behavioris stored for later review. In another embodiment, a securityadministrator is notified of the anomalous user behavior. However, if itwas determined in step 818 that the current user behavior element is notanomalous, then the current user behavior element is marked as maliciousin step 824, followed by the performance of malicious user behavioroperations in step 826. Thereafter, or once the current user behaviorelement has been marked as acceptable or anomalous in steps 816 or 820,the current user behavior element is appended to the user's userbehavior profile in step 828.

A determination is then made in step 830 whether to end user behaviormonitoring operations. If not, then the process continues, proceedingwith step 808. Otherwise, user behavior profile scoring operations,described in greater detail herein, are performed in step 832 togenerate a user behavior score. User behavior hashing operations,likewise described in greater detail herein, are then performed in step834 to generate a user behavior hash values. The resulting cyberbehavior score and hash value are then appended to the user's userbehavior profile in step 836. User behavior monitoring operations arethen ended in step 838.

As will be appreciated by one skilled in the art, the present inventionmay be embodied as a method, system, or computer program product.Accordingly, embodiments of the invention may be implemented entirely inhardware, entirely in software (including firmware, resident software,micro-code, etc.) or in an embodiment combining software and hardware.These various embodiments may all generally be referred to herein as a“circuit,” “module,” or “system.” Furthermore, the present invention maytake the form of a computer program product on a computer-usable storagemedium having computer-usable program code embodied in the medium.

Any suitable computer usable or computer readable medium may beutilized. The computer-usable or computer-readable medium may be, forexample, but not limited to, an electronic, magnetic, optical,electromagnetic, infrared, or semiconductor system, apparatus, ordevice. More specific examples (a non-exhaustive list) of thecomputer-readable medium would include the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a portable compact disc read-only memory (CD-ROM), anoptical storage device, or a magnetic storage device. In the context ofthis document, a computer-usable or computer-readable medium may be anymedium that can contain, store, communicate, or transport the programfor use by or in connection with the instruction execution system,apparatus, or device.

Computer program code for carrying out operations of the presentinvention may be written in an object oriented programming language suchas Java, Smalltalk, C++ or the like. However, the computer program codefor carrying out operations of the present invention may also be writtenin conventional procedural programming languages, such as the “C”programming language or similar programming languages. The program codemay execute entirely on the user's computer, partly on the user'scomputer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer or entirely on the remotecomputer or server. In the latter scenario, the remote computer may beconnected to the user's computer through a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Embodiments of the invention are described with reference to flowchartillustrations and/or block diagrams of methods, apparatus (systems) andcomputer program products according to embodiments of the invention. Itwill be understood that each block of the flowchart illustrations and/orblock diagrams, and combinations of blocks in the flowchartillustrations and/or block diagrams, can be implemented by computerprogram instructions. These computer program instructions may beprovided to a processor of a general purpose computer, special purposecomputer, or other programmable data processing apparatus to produce amachine, such that the instructions, which execute via the processor ofthe computer or other programmable data processing apparatus, createmeans for implementing the functions/acts specified in the flowchartand/or block diagram block or blocks.

These computer program instructions may also be stored in acomputer-readable memory that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory produce an article of manufacture including instruction meanswhich implement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer orother programmable data processing apparatus to cause a series ofoperational steps to be performed on the computer or other programmableapparatus to produce a computer implemented process such that theinstructions which execute on the computer or other programmableapparatus provide steps for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

The present invention is well adapted to attain the advantages mentionedas well as others inherent therein. While the present invention has beendepicted, described, and is defined by reference to particularembodiments of the invention, such references do not imply a limitationon the invention, and no such limitation is to be inferred. Theinvention is capable of considerable modification, alteration, andequivalents in form and function, as will occur to those ordinarilyskilled in the pertinent arts. The depicted and described embodimentsare examples only, and are not exhaustive of the scope of the invention.

Consequently, the invention is intended to be limited only by the spiritand scope of the appended claims, giving full cognizance to equivalentsin all respects.

What is claimed is:
 1. A computer-implementable method for generating acyber behavior profile, comprising: monitoring user interactions betweena user and an information handling system; converting the userinteractions into electronic information representing the userinteractions, the electronic information representing the userinteractions comprising multi-layered electronic information, each layerof the multi-layered electronic information corresponding to arespective layer of user interaction; and generating a uniquemulti-dimensional cyber behavior profile based upon the multi-layeredelectronic information representing the user interactions.
 2. The methodof claim 1, further comprising: associating the unique multi-dimensionalcyber behavior profile with the user.
 3. The method of claim 2, wherein:the monitoring user interactions comprises monitoring a plurality ofpoints of observability of the information handling system, at leastsome of the plurality of points of observability corresponding torespective layers of user interaction; and, each of the plurality ofpoints of observability is converted into respective electronicinformation representing respective points of observability.
 4. Themethod of claim 1, wherein: at least one of the respective layer of userinteractions correspond to temporal user interactions.
 5. The method ofclaim 1, wherein: the unique multi-dimensional cyber behavior profilecomprises a multi-faceted user behavior profile comprising a pluralityof facets, each of the plurality of facets corresponding to at least oneof a user authentication factor, a user identification factor and a userbehavior factor
 6. The method of claim 3, wherein: the plurality ofpoints of observability comprise an action based point of observability,activity based point of observability and behavior based point ofobservability.
 7. The method of claim 1, further comprising: identifyingthe interactions between the user and the information handling systemused for generating the unique cyber behavior profile as known goodbehavior; determining whether additional interactions identified asbetween the user and the information handling system do not correspondto the known good behavior; and, performing an enforcement operationwhen additional interactions identified as between the user and theinformation handling system do not correspond to the known goodbehavior.
 8. The method of claim 1, further comprising: storing theunique cyber behavior profile within a cyber behavior repository, thecyber behavior repository containing a plurality of unique cyberbehavior profiles, each the plurality of unique cyber behavior profilescorresponding to a respective user.
 9. The method of claim 8, furthercomprising: securing each of the plurality of unique cyber behaviorprofiles prior to storing within the cyber behavior repository.
 10. Themethod of claim 8, further comprising: monitoring an informationtechnology environment using the plurality of unique behavioralidentifiers; performing an enforcement operation if a user interactionwith the information technology environment does not correspond tointeractions based upon at least one of the plurality of unique cyberbehavior profiles.